Energy transfer and spatial scrambling of an exciton in a conjugated dendrimer.

Photoexcitation of multichromophoric light harvesting molecules induces a number of intramolecular electronic energy relaxation and redistribution pathways that can ultimately lead to ultrafast exciton self-trapping on a single chromophore unit. We investigate the photoinduced processes that take place on a phenylene-ethynylene dendrimer, consisting of nine equivalent linear chromophore units or branches. meta-Substituted links between branches break the conjugation giving rise to weak couplings between them and to localized excitations. Our nonadiabatic excited-state molecular dynamics simulations reveal that the ultrafast internal conversion process to the lowest excited state is accompanied by an inner → outer inter-branch migration of the exciton due to the entropic bias associated with energetically equivalent conjugated segments. The electronic energy redistribution among chromophore units occurs through several possible pathways in which through-bond transport and through-space exciton hopping mechanisms can be distinguished. Besides, triple bond excitations coincide with the localization of the electronic transition densities, suggesting that the intramolecular energy redistribution is a concerted electronic and vibrational energy transfer process.

ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost.

Deep learning is revolutionizing many areas of science and technology, especially image, text, and speech recognition. In this paper, we demonstrate how a deep neural network (NN) trained on quantum mechanical (QM) DFT calculations can learn an accurate and transferable potential for organic molecules. We introduce ANAKIN-ME (Accurate NeurAl networK engINe for Molecular Energies) or ANI for short. ANI is a new method designed with the intent of developing transferable neural network potentials that utilize a highly-modified version of the Behler and Parrinello symmetry functions to build single-atom atomic environment vectors (AEV) as a molecular representation. AEVs provide the ability to train neural networks to data that spans both configurational and conformational space, a feat not previously accomplished on this scale. We utilized ANI to build a potential called ANI-1, which was trained on a subset of the GDB databases with up to 8 heavy atoms in order to predict total energies for organic molecules containing four atom types: H, C, N, and O. To obtain an accelerated but physically relevant sampling of molecular potential surfaces, we also proposed a Normal Mode Sampling (NMS) method for generating molecular conformations. Through a series of case studies, we show that ANI-1 is chemically accurate compared to reference DFT calculations on much larger molecular systems (up to 54 atoms) than those included in the training data set.

Ultrafast electronic energy relaxation in a conjugated dendrimer leading to inter-branch energy redistribution.

Dendrimers are arrays of coupled chromophores, where the energy of each unit depends on its structure and conformation. The light harvesting and energy funneling properties are strongly dependent on their highly branched conjugated architecture. Herein, the photoexcitation and subsequent ultrafast electronic energy relaxation and redistribution of a first generation dendrimer (1) are analyzed combining theoretical and experimental studies. Dendrimer 1 consists of three linear phenylene-ethynylene (PE) units, or branches, attached in the meta position to a central group opening up the possibility of inter-branch energy transfer. Excited state dynamics are explored using both time-resolved spectroscopy and non-adiabatic excited state molecular dynamics simulations. Our results indicate a subpicosecond loss of anisotropy due to an initial excitation into several states with different spatial localizations, followed by exciton self-trapping on different units. This exciton hops between branches. The absence of an energy gradient leads to an ultrafast energy redistribution among isoenergetic chromophore units. At long times we observe similar probabilities for each branch to retain significant contributions of the transition density of the lowest electronic excited-state. The observed unpolarized emission is attributed to the contraction of the electronic wavefunction onto a single branch with frequent interbranch hops, and not to its delocalization over the whole dendrimer.

Steered Molecular Dynamics Methods Applied to Enzyme Mechanism and Energetics.

One of the main goals of chemistry is to understand the underlying principles of chemical reactions, in terms of both its reaction mechanism and the thermodynamics that govern it. Using hybrid quantum mechanics/molecular mechanics (QM/MM)-based methods in combination with a biased sampling scheme, it is possible to simulate chemical reactions occurring inside complex environments such as an enzyme, or aqueous solution, and determining the corresponding free energy profile, which provides direct comparison with experimental determined kinetic and equilibrium parameters. Among the most promising biasing schemes is the multiple steered molecular dynamics method, which in combination with Jarzynski's Relationship (JR) allows obtaining the equilibrium free energy profile, from a finite set of nonequilibrium reactive trajectories by exponentially averaging the individual work profiles. However, obtaining statistically converged and accurate profiles is far from easy and may result in increased computational cost if the selected steering speed and number of trajectories are inappropriately chosen. In this small review, using the extensively studied chorismate to prephenate conversion reaction, we first present a systematic study of how key parameters such as pulling speed, number of trajectories, and reaction progress are related to the resulting work distributions and in turn the accuracy of the free energy obtained with JR. Second, and in the context of QM/MM strategies, we introduce the Hybrid Differential Relaxation Algorithm, and show how it allows obtaining more accurate free energy profiles using faster pulling speeds and smaller number of trajectories and thus smaller computational cost.

Juvenile hormone synthesis: "esterify then epoxidize" or "epoxidize then esterify"? Insights from the structural characterization of juvenile hormone acid methyltransferase.

Juvenile hormones (JHs) play key roles in regulating metamorphosis and reproduction in insects. The last two steps of JH synthesis diverge depending on the insect order. In Lepidoptera, epoxidation by a P450 monooxygenase precedes esterification by a juvenile hormone acid methyltransferase (JHAMT). In Orthoptera, Dictyoptera, Coleoptera and Diptera epoxidation follows methylation. The aim of our study was to gain insight into the structural basis of JHAMT's substrate recognition as a means to understand the divergence of these pathways. Homology modeling was used to build the structure of Aedes aegypti JHAMT. The substrate binding site was identified, as well as the residues that interact with the methyl donor (S-adenosylmethionine) and the carboxylic acid of the substrate methyl acceptors, farnesoic acid (FA) and juvenile hormone acid (JHA). To gain further insight we generated the structures of Anopheles gambiae, Bombyx mori, Drosophila melanogaster and Tribolium castaneum JHAMTs. The modeling results were compared with previous experimental studies using recombinant proteins, whole insects, corpora allata or tissue extracts. The computational study helps explain the selectivity toward the (10R)-JHA isomer and the reduced activity for palmitic and lauric acids. The analysis of our results supports the hypothesis that all insect JHAMTs are able to recognize both FA and JHA as substrates. Therefore, the order of the methylation/epoxidation reactions may be primarily imposed by the epoxidase's substrate specificity. In Lepidoptera, epoxidase might have higher affinity than JHAMT for FA, so epoxidation precedes methylation, while in most other insects there is no epoxidation of FA, but esterification of FA to form MF, followed by epoxidation to JH III.

Coherent electron transport through an azobenzene molecule: a light-driven molecular switch.

We apply a first-principles computational approach to study a light-sensitive molecular switch. The molecule that comprises the switch can convert between a trans and a cis configuration upon photoexcitation. We find that the conductance of the two isomers varies dramatically, which suggests that this system has potential application as a molecular device. A detailed analysis of the band structure of the metal leads and the local density of states of the system reveals the mechanism of the switch.

A molecular dynamics study of Fe2S2 putidaredoxin: multiple conformations of the C-terminal region.

Putidaredoxin (Pdx) plays an essential role as an electron donor and effector in the biochemical cycle involving cytochrome P450cam. Only recently has an NMR-derived structure for this protein been published, but because of the presence of a paramagnetic Fe2S2 center, the NMR assignment could not be completed for residues within a region of 8 A around the active site. That region was modeled by homology with a related protein. The structural refinement for those experiments was done in vacuum, without the use of electrostatic terms in the force field. The present manuscript will describe and discuss a series of long-time, unrestrained, solution molecular dynamic runs for this system. Results will be presented that construct a molecular-level picture that rationalizes experimental results concerning the conformation and mobility of the C-terminal residue Trp106. At least two different conformers are found for this residue during the simulations. The time scale for interconversion between them is found to be in the subnanosecond regime. The results presented here open the possibility for studying binding and electron transfer between Pdx and P450cam, in a framework that allows for dynamical information to be used during the computational process, instead of the single structures deposited on the protein data base.